stat

Parameters

Parameter label

I/O type

Data type

Mandatory parameter?

Default value

inputVec

input

vector

yes

N/A

measure

input

string

no

"mean"

normalizeToDensity

input

bool

no

False

normalizeEntropy

input

bool

no

False

numberClasses

input

integer

no

None

circ_max

input

integer

no

None

outputVec

output

vector

N/A

N/A

Functionality

Module can compute the following statistical descriptors from inputVec based on the value of measure:

  • Minimum ("min")

  • Maximum ("max")

  • Range ("range") : max - min

  • Mean ("mean")

  • Variance ("var")

  • Standard deviation ("std")

  • Median ("median")

  • Entropy ("entropy"): Entropy of raw data vector

  • Entropy ("entropy_hist"): Entropy of a histogram

  • Zipf coefficient ("zipf_coefficient")

  • Circular mean (angle) ("circ_mean_angle")

  • Circular mean (length) (circ_mean_length")

  • Circular variance (circ_var")

  • Circular standard deviation (circ_std")

  • Circular dispersion (circ_disp")

If normalizeEntropy=True, the entropy is normalized to yield values between 0 and 1, by dividing by log N with is the maximum entropy for N classes. N can be given either explicitly by the parameter numberClasses or will be implicitly set as the observed number of different classes. The parameter normalizeToDensity is useful only for the entropy_hist-measure, which normalises raw bin counts to densities. Circular (directional) statististics are need for transformations such as pitch classes (i.e., derived from some modulo operation), see https://en.wikipedia.org/wiki/Directional_statistics for more details. For circular statistics, the circ_max parameter is used to map raw values onto the interval [0, 2\pi]. The Zipf coefficient is the (negative) slope of a linear regression on the log-log-plot of rank-ordered frequencies. It is the exponent of a fitted power (Zipf) law (see https://en.wikipedia.org/wiki/Zipf’s_law).